Database Specialist - Contract at PathAI

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Full Time

Start Date

Immediate

Expiry Date

08 Jan, 26

Salary

0.0

Posted On

10 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Relational Databases, ETL Processes, Big Data Deployments, Apache Airflow, Python, S3-Based Storage, Data Management, Query Optimization, Data Partitioning, Cost Optimization, Machine Learning, Data Governance, Retention Policies

Industry

Software Development

Description

Who We Are PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning. Our team, comprising diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact. We are seeking an experienced Contract Database / Data Warehouse Specialist to enhance the scalability, performance, and maintainability of our ML data infrastructure. The ideal candidate will bring expertise in relational databases, ETL processes, and modern big data deployments. You will work closely with our MLOps and ML engineering teams to optimize storage usage, modernize ETL pipelines, deploy new technology, and/or build / enhance tools that support analytics and machine learning workflows. Contract Duration: Minimum 6 months Location: Remote (U.S.) What You’ll Do Analyze and optimize storage strategies for ML experiment data and metadata. Design and implement intelligent retention and expiration for large-scale datasets. Modernize and refactor ETL pipelines to improve scalability and ease of maintenance. Build and enhance database-backed applications supporting ML R&D and production analytics. Collaborate with ML engineers, SREs, and platform teams. Provide knowledge transfer for long-term maintainers. What You’ll Need Proven expertise with relational databases (e.g., Postgres, Amazon RDS, Aurora), including schema design, query optimization, and performance tuning. Strong experience with ETL development and cloud data warehousing (e.g., Snowflake, Redshift). Familiarity with big data deployments and scalable architectures such as Spark and Hive. Experience with Apache Airflow for systems automation. Proficiency in Python for application development, data processing and automation. Understanding of S3-based storage and large-scale data management strategies. Ability to write clear technical documentation and collaborate effectively across teams. Experience with query optimization, data partitioning strategies, and cost optimization in cloud environments Nice to Have Background in machine learning data pipelines or analytics-heavy environments. Knowledge of data governance, retention policies, or cost-optimization strategies in cloud environments. We Want to Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for. PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. #LI-Remote

Responsibilities

The Database Specialist will analyze and optimize storage strategies for ML experiment data and metadata, and modernize ETL pipelines to improve scalability and maintenance. They will collaborate with ML engineers and platform teams to build and enhance database-backed applications supporting ML R&D and production analytics.